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Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Over the years, the significance of retrofitting has gained much attention with the unveiling of its different applications, such as energy retrofit and deep retrofit, to enhance the climate-resilience of buildings. However, no single study comprehensively assesses the climate-resilience of retrofitting. The purpose of this study is to address this gap via a systematic literature review.

Quality journal studies were selected using the PRISMA method and analysed manually and using scientometrics. Three dimensions of climate-resilience, such as robustness, withstanding and recovery, were used to evaluate the contribution of retrofit measures for achieving climate-resilient houses across four climate zones: tropical, arid, temperate and cold.

Most passive measures can enhance the robustness of residential buildings but cannot verify for withstanding against immediate shocks and timely recovery. However, some passive measures, such as night-time ventilation, show excellent performance over all four climate zones. Active measures such as heating, ventilation and air conditioning and mechanical ventilation with heat recovery, can ensure climate-resilience in all three dimensions in the short-term but contribute to greenhouse gas emissions, further exacerbating the long-term climate. Integrating renewable energy sources can defeat this issue. Thus, all three retrofit strategies should appropriately be adopted together to achieve climate-resilient houses.

Since the research is limited to secondary data, retrofit measures recommended in this research should be further investigated before application.

This review contributes to the knowledge domain of retrofitting by assessing the contribution of different retrofit measures to climate-resilience.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous pollutant. Soil contaminated with petroleum hydrocarbons adversely affects the properties of soil. This paper aim to remove pollutants from the environment is an urgent need of the hour to maintain the proper functioning of soil ecosystems.

The ability of micro-organisms to degrade petroleum hydrocarbons makes it possible to use these microorganisms to clean the environment from petroleum pollution. For preparing this review, research papers and review articles related to petroleum hydrocarbons degradation by micro-organisms were collected from journals and various search engines.

Various physical and chemical methods are used for remediation of petroleum hydrocarbons contaminants. However, these methods have several disadvantages. This paper will discuss a novel understanding of petroleum hydrocarbons degradation and how micro-organisms help in petroleum-contaminated soil restoration. Bioremediation is recognized as the most environment-friendly technique for remediation. The research studies demonstrated that bacterial consortium have high biodegradation rate of petroleum hydrocarbons ranging from 83% to 89%.

Proper management of petroleum hydrocarbons pollutants from the environment is necessary because of their toxicity effects on human and environmental health.

This paper discussed novel mechanisms adopted by bacteria for biodegradation of petroleum hydrocarbons, aerobic and anaerobic biodegradation pathways, genes and enzymes involved in petroleum hydrocarbons biodegradation.

This paper aims to compare the wear behavior, surface roughness, friction coefficient and volume loss of high-velocity oxy-fuel (HVOF) sprayed WC–Co and WC–Cr₃C₂–Ni coatings on AISI 1095 steel with spraying times of 10 and 15 s.

In this study, the pin-on-disc testing technique was used to evaluate the wear characteristics at a speed of 0.24 m/s, load of 40 N and test time of 60 min under dry conditions at room temperature. The wear characteristics were examined and analyzed by scanning electron microscopy and energy dispersive X-ray spectroscopy. The surface roughness of a coated surface was measured, and microhardness measurements were performed on the cross-sectioned and polished surfaces of the coating.

Spraying time and powder material affected the hardness of HVOF coatings due to differences in the porosity of the coated layers. The average hardness of the WC–Cr₃C₂–Ni coating with a spaying time of 15 s was approximately 14% higher than that of the WC–Cr₃C₂–Ni coating with a spraying time of 10 s. Under an applied load of 40 N, the WC–Co coating with a spraying time of 15 s had the lowest variation in the friction coefficient compared with the other coatings. The WC–Co coating with a spraying time of 10 s had the lowest average and variation in volume loss compared to the other coatings. The WC–Cr₃C₂–Ni coating with a spraying time of 10 s exhibited the highest average volume loss. The wear features changed slightly with the spraying time owing to variations in the hardness and friction coefficient.

This study investigated tribological performance of WC–Co; WC-Cr₃C₂-Ni coatings with spraying times of 10 and 15 s using pin-on-disc tribometer by rotating the relatively soft pin (C45 steel) against hard coated substrate (disc).

Inclination angle has been reported to have an enhancing effect on the thermal-hydraulic characteristics and entropy of some thermal systems. Therefore, this paper aims to numerically investigate the effects of inclination angle, volume concentration and Reynolds number on the thermal and hydraulic characteristics and entropy generation rates of water-based Al₂O₃ nanofluids through a smooth circular aluminum pipe in a turbulent flow.

A constant heat flux of 2,000 Watts is applied to the circular surface of the tube. Reynolds number is varied between 4,000 and 20,000 for different volume concentrations of alumina nanoparticles of 0.5%, 1.0% and 2.0% for tube inclination angles of ±90o, ±60o, ±45o, ±30o and 0o, respectively. The simulation is performed in an ANSYS Fluent environment using the realizable kinetic energy–epsilon turbulent model.

Results show that +45o tube orientation possesses the largest thermal deviations of 0.006% for 0.5% and 1.0% vol. concentrations for Reynolds numbers 4,000 and 12,000. −45o gives a maximum pressure deviation of −0.06% for the same condition. The heat transfer coefficient and pressure drop give maximum deviations of −0.35% and −0.39%, respectively, for 2.0% vol. concentration for Reynolds number of 20,000 and angle ±90o. A 95%–99.8% and 95%–98% increase in the heat transfer and total entropy generation rates, respectively, is observed for 2.0% volume concentration as tube orientation changes from the horizontal position upward or downward.

Research investigating the effect of inclination angle on thermal-hydraulic performance and entropy generation rates in-tube turbulent flow of nanofluid is very scarce in the literature.

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.

This study aims to perform innovation analysis for a product based on market, design and process dimensions. This integrated approach provides sustainability for product design and development.

A significant aspect of innovation is investigated to provide energy from the wastes collected in the reverse chain. First, the indicators related to the product opportunity gap were collected and ranked by the structural equation modeling (SEM) method. Indicators with a factor loading above 0.6 are selected and inserted into the proposed mathematical model. The proposed mathematical model was implemented in GAMS 28.2.0 to maximize energy production from waste and minimize the cost of product innovation. A case study on pistachio new packaging process innovation is investigated.

The results showed that in today’s competitive world where sustainability and the environment are important, the index of converting waste into energy is one of the main indicators of innovation. Consequently, flammability is extracted from the mathematical model as one of the most significant indicators leading to higher energy production with the lowest innovation cost.

New product development (NPD) is significant to sustain market share and satisfy customer needs. Different approaches are proposed to handle NPD, mostly focusing on the customer and design requirements.

Due to land resource scarcity, sustainable urban development in high-density cities has long been challenging. As such, many cities are formulating plans to “dig deep”, resulting in more citizens working and/or staying underground for longer periods of time. However, owing to the particularities of underground space, the factors involved in the creation of a healthy environment are different from those involved in aboveground developments. This study thus aims to investigate the influences of various underground environment factors on users' health through a holistic approach.

To achieve this aim, 12 underground sites and 12 corresponding aboveground sites are selected for a large-scale questionnaire survey, resulting in 651 survey samples. The survey covers post-occupancy evaluation of health (physical and psychosocial), underground environmental quality (visual, thermal, acoustic comfort, indoor air quality and ventilation), space design and greenery. Independent-sample T-test, Pearson correlation, multiple regression modelling and structural equation modelling are used to investigate whether significant differences exist between health of underground and aboveground users, and to develop an underground environment-health model for unveiling the significant associations between underground environment factors and users' health. To cross validate the results, an objective field measurement study is further conducted on six underground sites. The objective measurement results are used to cross validate the survey results.

The questionnaire results provide the following evidence: (1) health of underground users is significantly poorer than that of their aboveground counterparts; (2) underground development users' health is significantly affected by space design, greenery and environmental quality in terms of thermal comfort, indoor air quality, ventilation and acoustic comfort but not visual comfort; and (3) amongst the various identified factors, space design has the strongest predicting effects on human health. The field study echoes the survey findings and further unveils the relationships between different environmental factors and human health.

The results shed light on the importance of distinguishing between underground developments and aboveground ones in various guidelines and standards, especially those related to space management.

The purpose of this study was to improve the overall equipment effectiveness (OEE) of the production process of the shredder operation of ABC company, an industrial waste management company which supplies pre-processed industrial waste as alternative fuel to a cement plant.

This case study investigated all possible availability and performance losses that caused the shredder system’s OEE and various problem-solving techniques, such as root cause analysis and Pareto analysis, were used to find the root cause of the reduced OEE.

After analysing this case study, three significant loss factors were identified from all the availability and performance losses, which caused the shredder system’s OEE losses. Practical solutions were found for the effect of those loss factors to improve the machine’s OEE and productivity.

This case study has been concentrated on only analysing of losses and improvement of OEE in the production process and not about cost analysis between loss and improvements.

This paper shows how to improve the OEE of a production process through various problem-solving techniques by identifying its losses and how to achieve the best solutions for those losses in a practical manner.